Cybersecurity is one of the most important issues in the modern world. Cyberattacks are becoming increasingly sophisticated and destructive, and traditional cybersecurity methods are often not able to withstand them.
Artificial intelligence (AI) has significant potential to improve cybersecurity. It can be used for detection, prevention, and recovery from cyberattacks.
Opportunities for AI in Cybersecurity
AI in the field of cybersecurity is characterized by a number of key opportunities. First, AI is used to create immune systems that are able to adapt to new types of threats and even anticipate their evolution. This is becoming increasingly important in light of the constantly growing volume of cyber threats and their complexity.
It is also worth noting that AI can significantly improve the speed of response to cyber threats. The ability to automatically respond and take appropriate measures can save important data and systems from malicious effects.
Finally, the development of AI in cybersecurity also opens up new prospects for collective threat analysis and information sharing between different organizations. The introduction of modern AI tools can help to create common approaches to countering threats, which improves the overall state of cybersecurity.
AI can be used to detect cyberattacks at different levels.
At the network level, AI can be used to detect anomalies in network traffic that may indicate a cyberattack. One example of the use of AI to detect anomalies in network traffic is the DeepSight system from Cisco. This system uses artificial intelligence to detect anomalies in network traffic that may indicate various types of cyberattacks, including DDoS attacks, spoofed DNS attacks, and spoofed DHCP attacks.
AI can also be used to recover from cyberattacks, specifically to detect and remove malicious code that was downloaded during a cyberattack. One of the systems for recovery after cyberattacks is the Mandiant Threat Intelligence system.
At the system level, AI is a valuable tool for detecting malicious code on computers and servers.
An example of the use of AI to detect malicious code is the Sophos Deep Learning Malware Protection system. This system uses artificial intelligence to detect malicious code that does not contain known signatures.
At the user level, AI can be used to detect phishing attacks and other social engineering attacks.
One example of the use of AI to detect phishing attacks is the PhishMe system. This system uses artificial intelligence to detect phishing attacks that use certain social engineering techniques. The PhishMe system can also be used to train users to recognize phishing attacks. The system uses artificial intelligence to create realistic phishing messages that can be used to train users.
Challenges for AI in Cybersecurity
Despite its significant potential, AI also has a number of challenges that need to be overcome before it can fully realize its potential in cybersecurity.
One of the main challenges is data availability. AI needs a large amount of data about cyberattacks to train. However, this data is often rare and valuable, so it is difficult to obtain.
Another challenge is transparency. AI is often opaque, which makes it difficult to understand how it works and how it makes decisions. This can lead to problems with accountability and responsibility. There is also a risk that AI can be abused. For example, AI can be used to develop more effective cyberattacks.
Prospects for the Development of AI in Cybersecurity
It is expected that AI will play an increasingly important role in cybersecurity in the future. AI will be used to develop new methods for detecting and preventing cyberattacks. AI will also be used to automate cybersecurity tasks, which will free up time and resources for other tasks.
Conclusions
On the way to building a safe AI in cybersecurity, it is important to focus on the development of effective control mechanisms and ethical standards. This will not only protect against possible threats, but will also contribute to the creation of a reliable and globally accepted AI system.
Active cooperation at the international level, defining security standards, and educating the public about the use of AI in cybersecurity are critical components that will contribute to the creation of a sustainable and ethical digital future.
References:
1. "How Artificial Intelligence Is Changing Cybersecurity," by David J. Evans, in Computer Weekly, 2022.
2. "The Future of Artificial Intelligence in Cybersecurity," by Gartner, 2022.
3. "Artificial Intelligence for Cybersecurity: A Review of the State of the Art," by S.M.A.R.T. Team, in arXiv preprint arXiv:2205.09522, 2022.
4. "The Impact of Artificial Intelligence on Cybersecurity," by Forrester Research, 2022.
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Language advisor: Natalia B. Zjubanova, senior lecturer of Foreign Languages Department, National Aerospace University named after N. E. Zhukovsky "Khàrk³v Aviation Institute"
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